About this Video

• Video Title: This marketing agent automates EVERYTHING (free n8n template)
• Channel: Rory Ridgers
• Speakers: Rory Ridgers
• Duration: 00:24:48

Introduction

This video demonstrates how to create a fully autonomous marketing AI agent using n8n. The agent automates social media content creation, either on request or completely on autopilot. The creator provides a free template for viewers to use.

Key Takeaways

• A step-by-step guide on building an automated marketing AI agent with n8n is provided.
• The agent uses various tools and APIs, including Google search, Instagram scraping (via Amplify), and LLMs for content generation and summarization.
• The agent can generate blog posts and various social media posts (LinkedIn, Instagram, X, etc.).
• A custom-branded interface, built using the creator's platform, is shown for easy interaction with the agent.
• A free template for the n8n workflow and access to the creator's platform are offered.

The video details building an automated marketing AI agent within n8n. It doesn't provide exact, replicable steps for every user, as API keys and specific account details are involved, but it outlines the workflow's structure and functionality. Here's a comprehensive breakdown based on the transcript:

I. System Overview and Data Acquisition:

1. Input: The process begins with user input specifying the desired content (e.g., "Create a LinkedIn post about AI in healthcare").

2. Query Generation: An LLM (Large Language Model) refines the user input into a precise search query suitable for Google or Tavily searches (a Google API alternative).

3. Google Search (Tavily): A Tavily search is performed using the refined query. The API call includes setting the method to 'POST', providing the URL, authorization (API key), content type (application/JSON), and the search query in JSON format. The resulting URL from the top search result is retrieved.

4. Website Scraping: A GET request retrieves the HTML content from the URL obtained in the previous step. This HTML is converted into Markdown for easier processing by subsequent LLMs.

5. Instagram Scraping (Amplify): Amplify's Instagram post scraper is used to gather data from pre-selected AI news pages. The specific pages are hardcoded into the workflow. The API call uses the ‘run actor’ endpoint and retrieves the last 20 posts from each page, resulting in about 80 data items. The relevant data points (caption, comment count, first comment) are extracted.

6. Data Aggregation: The data from both Google search and Instagram scraping is combined. All captions, comment counts, and first comments are aggregated into single variables for further processing.

II. Content Generation:

1. Summarization (LLMs): Three separate LLM steps summarize the data. The first summarizes the scraped website content. The second summarizes the aggregated Instagram data. A third LLM then combines these summaries to provide a single overview of relevant information.

2. Content Type Determination (LLM): An LLM analyzes the initial user input to determine whether the user wants a blog post or social media posts. This uses a simple "if" statement to check if "blog" is in the output.

3. Blog Post Generation:

   • Planning: An LLM generates a blog post outline (sections and bullet points) based on the combined summary and the user's prompt.
   • Writing: Another LLM expands the outline into a complete blog post.
   • Google Sheets Integration: A Google Sheets node populates a spreadsheet with the blog post title, summary, content, and image URL (generated later).

4. Social Media Post Generation:

   • Image Generation: A workflow is triggered to generate an image. An LLM creates a structured prompt for the OpenAI image generation model (presumably DALL-E 2) based on the overall summary. The generated image is converted to a file and uploaded to Google Drive. Only the Google Drive web view link of the image is passed back to the main workflow to avoid sending large amounts of data.
   • Post Creation: An LLM generates a title, caption (including hashtags), and uses the Google Drive image URL to create the social media post.
   • Google Sheets Integration: The Google Sheets node adds the platform (defined in the user prompt), title, caption, image URL, and date to the spreadsheet.

III. Interface and Delivery:

1. Custom Interface (Commerce Agents): The creator’s platform, Commerce Agents, is used to create a custom web interface for interacting with the n8n agent. This interface allows users to input requests and receive the generated content.

2. Webhooks: Webhooks connect the n8n workflow to the Commerce Agents interface. The interface receives the AI agent's output (the created posts and any error messages).

3. Client Delivery (Optional): Commerce Agents facilitates the delivery of the custom interface to clients, providing password-protected access for each client.

Types of Posts Created:

The agent can create:

• Blog posts (with title and summary).
• Social Media posts (including LinkedIn, Instagram, X posts) with titles, captions (including hashtags), and an accompanying image.

Note: The video focuses on the workflow's structure. Implementing this requires setting up API keys, configuring nodes correctly, and potentially adjusting prompts to fine-tune the LLMs’ output. The provided transcript is a detailed explanation of the process, but it is not a direct step-by-step instruction manual ready for immediate replication. You will need programming knowledge and familiarity with the used tools.